{"id":2485,"date":"2025-02-04T14:15:21","date_gmt":"2025-02-04T10:15:21","guid":{"rendered":"https:\/\/biodiversity-armenia.am\/?page_id=2485"},"modified":"2026-02-21T16:36:20","modified_gmt":"2026-02-21T12:36:20","slug":"floods","status":"publish","type":"page","link":"https:\/\/biodiversity-armenia.am\/en\/seea-ea\/ongoing-projects\/preliminary-results-on-ea\/floods\/","title":{"rendered":"Floods"},"content":{"rendered":"\n

We apologize for possible errors in the machine translation of the site<\/mark><\/em><\/p>\n\n\n\n

Flood Risk Mitigation<\/strong> (InVEST UFRM model)<\/p>\n\n\n\n

GIS modeling and analysis, presentation of results – Eduard Kazakov<\/strong> (NextGIS O\u00dc, Estonia);
Analysis and presentation of results – Elena Bukvareva<\/strong> (BCC-Armenia);
Assessment of the alignment of results with real watersheds in Armenia – Vardan Asatryan<\/strong> (NAS RA) 
Assessment of the relevance of modeling results for Armenia – external expert Alexander Arakelyan<\/strong> (NAS RA) <\/p>\n\n\n\n

The InVEST model Urban Flood Risk Mitigation (UFRM<\/a>) calculates two main indicators:
– the Runoff retention<\/strong>, i.e. the amount of runoff retained by soil and vegetation compared to the storm rain volume in m3 (1 m3 of runoff is equal to 10 mm per one 10x10m pixel) and as proportion of retained precipitation);
– the Runoff (Q)<\/strong>, mm, which is a potentially hazardous factor that can cause flooding.<\/p>\n\n\n\n

This section presents preliminary results of testing models for assessing and mapping ecosystem services. In the future, if a decision is made to use these models, they should be calibrated using hydrological measurements made in Armenia.
The methodology and results will be described in detail in a forthcoming publication<\/em>.<\/em><\/p>\n\n\n\n

ES provided by terrestrial ecosystems<\/strong><\/p>\n\n\n\n

We tested the model for two scenarios\u2014average and extreme spring rainfall. The highest precipitation in Armenia occurs in May and June. While precipitation levels vary significantly across different climatic zones, for the initial model testing, we considered it reasonable to use countrywide average values. During these months, an average rainfall event delivers 12 mm of precipitation. For the extreme rainfall scenario, we assumed approximately half of the monthly precipitation in either of these months, which is 50 mm (Table 31A4-1).

Table 31A4-1. Precipitation and the number of days with rain in selected cities <\/strong>(http:\/\/armenia.pogoda360.ru\/<\/a>1<\/sup><\/a>)<\/p>\n\n\n\n

Climate zones<\/em><\/td>Cities<\/em><\/td>May<\/em><\/td>June<\/em><\/td><\/td><\/tr>
Days with rain<\/em><\/td>Precipi-tation, mm<\/em><\/td>Average rain, mm<\/em><\/td>Days with rain<\/em><\/td>Precipi-tation, mm<\/em><\/td>Average rain, mm<\/em><\/td>Catastrophic rain, mm (50% of monthly precipitation)<\/em><\/td><\/tr>
Moderate cool<\/td>Sevan<\/td>12<\/td>140<\/td>12<\/td>13<\/td>157<\/td>12<\/td>79<\/td><\/tr>
Hrazdan<\/td>10<\/td>113<\/td>11<\/td>10<\/td>120<\/td>12<\/td>60<\/td><\/tr>
Stepanavan<\/td>11<\/td>141<\/td>13<\/td>10<\/td>130<\/td>13<\/td>65<\/td><\/tr>
Vanadzor<\/td>13<\/td>177<\/td>14<\/td>13<\/td>189<\/td>15<\/td>95<\/td><\/tr>
Average<\/td>12<\/td>143<\/td>12<\/td>12<\/td>149<\/td>13<\/td>75<\/td><\/tr>
Moderate relatively humid<\/td>Idjevan<\/td>10<\/td>127<\/td>13<\/td>8<\/td>97<\/td>12<\/td>64<\/td><\/tr>
Dilijan<\/td>11<\/td>133<\/td>12<\/td>12<\/td>133<\/td>11<\/td>67<\/td><\/tr>
Alaverdi<\/td>10<\/td>134<\/td>13<\/td>8<\/td>100<\/td>13<\/td>67<\/td><\/tr>
Goris<\/td>9<\/td>103<\/td>11<\/td>5<\/td>63<\/td>13<\/td>52<\/td><\/tr>
Average<\/td>10<\/td>124<\/td>12<\/td>8<\/td>98<\/td>12<\/td>62<\/td><\/tr>
Arid<\/td>Armavir<\/td>7<\/td>33<\/td>5<\/td>7<\/td>28<\/td>4<\/td>17<\/td><\/tr>
Ararat<\/td>2<\/td>39<\/td>20<\/td>1<\/td>20<\/td>20<\/td>20<\/td><\/tr>
Meghri<\/td>6<\/td>81<\/td>14<\/td>3<\/td>44<\/td>15<\/td>41<\/td><\/tr>
Average<\/td>5<\/td>51<\/td>10<\/td>4<\/td>31<\/td>8<\/td>26<\/td><\/tr>
Moderate with dry summer<\/td>Gyumri<\/td>6<\/td>78<\/td>13<\/td>5<\/td>71<\/td>14<\/td>39<\/td><\/tr>
Gavar<\/td>13<\/td>147<\/td>11<\/td>13<\/td>166<\/td>13<\/td>74<\/td><\/tr>
Vardenis<\/td>9<\/td>109<\/td>12<\/td>9<\/td>99<\/td>11<\/td>55<\/td><\/tr>
Sisian<\/td>8<\/td>112<\/td>14<\/td>7<\/td>84<\/td>12<\/td>56<\/td><\/tr>
Average<\/td>9<\/td>112<\/td>12<\/td>9<\/td>105<\/td>12<\/td>56<\/td><\/tr>
Average<\/td><\/td>9<\/td>110<\/td>12<\/td>8<\/td>99<\/td>12<\/td>48<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

ES provided by terrestrial ecosystems: the average spring rainfall scenario (12 mm)<\/strong><\/strong><\/p>\n\n\n\n

ES maps (Figure 31A4-1) show that precipitation is almost entirely retained by vegetation and soil. Quick runoff across most of Armenia is less than 1 mm, slightly exceeding this value in some valleys. Under the bare ground scenario (all natural vegetation is replaced with bare soil), runoff retention (RT) reduces very slightly. Quick runoff (Q) increases slightly in absolute terms, but the relative changes in some watersheds are noticeable.\"\"
Figure 31A4-1. Maps of ES indicators under the average spring rainfall scenario (12 mm). For detailed maps see the section “Ecosystem Services – Urban Flood Risk Mitigation \u2013 Average rainfall (12 mm)<\/a> in the progect WebGIS<\/strong>

The ES provided by natural terrestrial ecosystems estimated as the difference in indicators between the ES on current land cover 2023 and on bare ground scenario. The influence of ecosystems on ES indicators is minor, amounting to a decrease in quick runoff by 0.01\u20130.08 mm and an increase in runoff retention by 1\u20138 liters per pixel; for the Hrazdan watershed a very small but opposite effect is observed. In relative terms, the effect on runoff retention is extremely small\u2014everywhere under 1% of the 2023 value\u2014and there is a wide spread in the share of quick runoff changes, ranging from +55% to -3%. (Table 31A4-2; Figures 31A4-2 and 31A4-3).

\"\"Figure 31A4-2. Ecosystem effect on quick runoff and runoff retention across watersheds under the average spring rainfall scenario (12 mm)<\/strong>.\"\"Figure 31A4-3. Ecosystem effect on quick runoff and runoff retention reltive to ES on current land cover (2023), %<\/strong><\/p>\n\n\n\n

Table 31A4-2. ES indicators across watersheds under the average rainfall scenario (12 mm)<\/strong><\/p>\n\n\n\n

<\/td>Indicator<\/em><\/td>Aghstev<\/em><\/td>Akhu<\/em>ryan<\/em><\/td>Arpa<\/em><\/td>Debed<\/em><\/td>Hraz<\/em>dan<\/em><\/td>Metsa<\/em>mor<\/em><\/td>Voro<\/em>tan<\/em><\/td><\/tr>
Current land cover, ESRI 2023<\/td>Quick flow, mm, Q2023<\/sub><\/td>0.11<\/td>0.40<\/td>0.16<\/td>0.10<\/td>0.24<\/td>0.27<\/td>0.07<\/td><\/tr>
Runoff retention, m3<\/sup>\/pix, RT2023<\/sub><\/td>1.19<\/td>1.16<\/td>1.18<\/td>1.19<\/td>1.18<\/td>1.17<\/td>1.19<\/td><\/tr>
Total runoff retention, mln of m3<\/sup>, RT2023Tot<\/sub><\/td>37.76<\/td>32.07<\/td>52.19<\/td>46.71<\/td>70.43<\/td>42.78<\/td>53.42<\/td><\/tr>
Bare ground scenario<\/td>Quick flow, mm, Qbare<\/sub><\/td>0.19<\/td>0.41<\/td>0.16<\/td>0.16<\/td>0.26<\/td>0.26<\/td>0.13<\/td><\/tr>
Runoff retention, m3<\/sup>\/pix, RTbg<\/sub><\/td>1.18<\/td>1.16<\/td>1.18<\/td>1.18<\/td>1.17<\/td>1.17<\/td>1.19<\/td><\/tr>
Total runoff retention, mln of m3<\/sup>, RTbgTot<\/sub><\/td>37.51<\/td>32.04<\/td>52.16<\/td>46.49<\/td>70.30<\/td>42.81<\/td>53.16<\/td><\/tr>
Effect of terrestrial eco-systems<\/td>Reduction of quick runoff by ecosys-tems, mm
Qeco<\/sub> =
Q2023<\/sub>-Qbg<\/sub><\/td>		-0.06<\/td>-0.08<\/td>-0.01<\/td>-0.06<\/td>0.01<\/td>-0.02<\/td>-0.01<\/td><\/tr>
Share of Q reduced by ecosystems, %
Qeco<\/sub>*100\/
Q2023<\/sub><\/td>		-54.88<\/td>-19.81<\/td>-3.94<\/td>-54.91<\/td>3.05<\/td>-8.13<\/td>-13.14<\/td><\/tr>
Runoff retention, provided by ecosystems, m3\/pix
RTeco<\/sub> =
RT2023<\/sub>-RTbg<\/sub><\/td>		0.01<\/td>0.01<\/td>0.00<\/td>0.01<\/td>0.00<\/td>0.00<\/td>0.00<\/td><\/tr>
Share of RT provided by ecosystems, %
RTeco<\/sub>*100\/
RT2023<\/sub><\/td>		0.50<\/td>0.69<\/td>0.05<\/td>0.47<\/td>-0.06<\/td>0.18<\/td>0.08<\/td><\/tr>
Total runoff retention, provided by ecosystems, mln of m3<\/sup> RTecoTot<\/sub> =
RT2023Tot<\/sub> -RTbgTot<\/sub><\/td>		0.26<\/td>0.25<\/td>0.03<\/td>0.22<\/td>-0.03<\/td>0.13<\/td>0.03<\/td><\/tr>
Share of total RT, provided by ecosystems RTecoTot<\/sub>*100\/RT2023Tot<\/sub><\/td>0.70<\/td>0.79<\/td>0.05<\/td>0.47<\/td>-0.04<\/td>0.30<\/td>0.05<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

ES provided by terrestrial ecosystems: the extreme spring rainfall scenario (50 mm)<\/strong><\/strong><\/p>\n\n\n\n

Precipitation is fully retained only in a small part of the territory (the darkest areas on the map of runoff retention). As a result, quick runoff exceeds 10 mm across most of the territory and exceeds 20 mm in a significant portion. If all natural vegetation is replaced with bare ground, runoff retention decreases significantly, and quick runoff also increases noticeably. Unlike the average-rain scenario, under an extreme-rain event the ecosystems\u2019 influence on the ES indicators is substantial: they reduce quick runoff by an average of 4 mm (\u221232% relative to the value in 2023) and increase runoff retention by 0.4 m\u00b3\/pix (+11% relative to the value in 2023). Totally, ecosystems increase runoff retention by 118 millions of m\u00b3\"\"
Figure 31A4-4. Maps of ES indicators under the extreme spring rainfall scenario (50 mm). For detailed maps see the section “Ecosystem Services – Urban Flood Risk Mitigation \u2013 Extreme rainfall (50 mm)<\/a> in the progect WebGIS<\/strong>

Ecosystems increase runoff retention across all watersheds by 0.3\u20130.5 m\u00b3 and reduce quick runoff by 2.9\u20135.3 mm (Fig. 31A4-5; Table 31A4-3). In relative terms, compared to 2023 values, the ecosystem effect is most pronounced in the Arpa and Vorotan watersheds, where runoff retention increased by 13% and quick runoff decreased by 43\u201349% (Fig. 31A4-6; Table 31A4-3).

\"\"Figure 31A4-5. ES indicators under the extreme spring rainfall scenario (50 mm)<\/strong><\/strong> across watersheds<\/strong>

\"\"Figure 31A4-6. Ecosystem effect: percentage change in runoff retention (R) and quick runoff (P) relative to 2023, by watershed<\/strong><\/p>\n\n\n\n

Table 31A4-3. ES indicators across watersheds under the extreme rainfall scenario (50 mm)<\/strong><\/p>\n\n\n\n

<\/td>Indicator<\/em><\/td>Aghstev<\/em><\/td>Akhu<\/em>–<\/em>ryan<\/em><\/td>Arpa<\/em><\/td>Debed<\/em><\/td>Hraz<\/em>–<\/em>dan<\/em><\/td>Metsa<\/em>–<\/em>mor<\/em><\/td>Voro<\/em>–<\/em>tan<\/em><\/td><\/tr>
Current land cover, ESRI 2023<\/td>Quick flow, mm, Q2023<\/sub><\/td>13.3<\/td>16.6<\/td>10.8<\/td>13.3<\/td>13.4<\/td>14.3<\/td>11.7<\/td><\/tr>
Runoff retention, m3<\/sup>\/pix, RT2023<\/sub><\/td>3.7<\/td>3.3<\/td>3.9<\/td>3.7<\/td>3.7<\/td>3.6<\/td>3.8<\/td><\/tr>
Total runoff retention, mln of m3<\/sup>, RT2023Tot<\/sub><\/td>116<\/td>92<\/td>173<\/td>144<\/td>219<\/td>130<\/td>172<\/td><\/tr>
Bare ground scenario<\/td>Quick flow, mm, Qbare<\/sub><\/td>17.7<\/td>19.5<\/td>16.0<\/td>17.6<\/td>17.1<\/td>17.4<\/td>16.7<\/td><\/tr>
Runoff retention, m3<\/sup>\/pix, RTbg<\/sub><\/td>3.2<\/td>3.1<\/td>3.4<\/td>3.2<\/td>3.3<\/td>3.3<\/td>3.3<\/td><\/tr>
Total runoff retention, mln of m3<\/sup>, RTbgTot<\/sub><\/td>103<\/td>84<\/td>150<\/td>127<\/td>197<\/td>119<\/td>149<\/td><\/tr>
Effect of terrestrial eco-systems<\/td>Reduction of quick runoff by ecosystems, mm Qeco<\/sub> = Q2023<\/sub> -Qbg<\/sub><\/td>-4.4<\/td>-2.9<\/td>-5.3<\/td>-4.3<\/td>-3.7<\/td>-3.1<\/td>-5.1<\/td><\/tr>
Share of Q reduced by ecosystems, %
Qeco<\/sub>*100\/ Q2023<\/sub><\/td>		-32.8<\/td>-17.4<\/td>-49.0<\/td>-32.0<\/td>-27.5<\/td>-21.8<\/td>-43.3<\/td><\/tr>
Runoff retention provided by ecosystems, m3<\/sup>\/pix
RTeco<\/sub> =
RT2023<\/sub> -RTbg<\/sub><\/td>		0.4<\/td>0.3<\/td>0.5<\/td>0.4<\/td>0.4<\/td>0.3<\/td>0.5<\/td><\/tr>
Share of RT provided by ecosystems, %
RTeco<\/sub>*100\/
RT2023<\/sub><\/td>		11.9<\/td>8.6<\/td>13.4<\/td>11.6<\/td>10.1<\/td>8.7<\/td>13.2<\/td><\/tr>
Total runoff retention, provided by ecosystems, mln of m3<\/sup> RTecoTot<\/sub> = RT2023Tot<\/sub> -RTbgTot<\/sub><\/td>14<\/td>8<\/td>23<\/td>17<\/td>22<\/td>11<\/td>23<\/td><\/tr>
Share of total RT, provided by ecosystems RTecoTot<\/sub>*100\/RT2023Tot<\/sub><\/td>11.9<\/td>8.6<\/td>13.4<\/td>11.6<\/td>10.1<\/td>8.7<\/td>13.2<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Changes in ES<\/strong><\/p>\n\n\n\n

Land-cover changes from 2017 to 2023, as captured in ESRI data, resulted in negative changes across all watersheds except Arpa. The most pronounced negative changes are modeled for the Akhuryan watershed, where runoff retention decreased by 1.5% and quick runoff increased by 3.8%. In the other watersheds (except Arpa), runoff retention decreased by 0.1\u20130.7%, while quick runoff increased by 0.3\u20131.5% (Figure31A4-7; Table 31A4-4). Changes in ES at the marz level mirror those at the watershed level. The changes are negative everywhere except in Vayots Dzor marz. The most pronounced negative changes are modeled for Shirak marz, which lies within the Akhuryan watershed (Figure 31A4-8; Table 31A4-4).\"\"Figure 31A4-7. Changes in ES under the extreme rainfall scenaio (50 mm) from 2017 to 2023 across watersheds<\/strong>

\"\"Figure 31A4-8. Changes in ES under the extreme rainfall scenaio (50 mm) from 2017 to 2023 across marzes<\/strong><\/p>\n\n\n\n

Table 31A4-4. Changes in ES under the extreme rainfall scenaio (50 mm) from 2017 to 2023<\/strong> <\/p>\n\n\n\n

EAA<\/em><\/td>Changes in absolute terms<\/em><\/td>Changes relative to the values in 2017, %<\/em><\/em><\/td><\/tr>
Quick runoff, Q, mm<\/em><\/td>Runoff retention, RT, m3<\/sup>\/pi<\/em>x<\/em><\/td>Quick runoff, Q<\/em><\/td>Runoff retention, RT<\/em><\/td><\/tr>
Watersheds<\/td>Aghstev<\/td>0.037<\/td>-0.001<\/td>0.315<\/td>-0.096<\/td><\/tr>
Akhuryan<\/td>0.545<\/td>-0.011<\/td>3.822<\/td>-1.526<\/td><\/tr>
Arpa<\/td>-0.012<\/td>0.000<\/td>-0.091<\/td>0.034<\/td><\/tr>
Debed<\/td>0.168<\/td>-0.003<\/td>1.262<\/td>-0.460<\/td><\/tr>
Hrazdan<\/td>0.147<\/td>-0.003<\/td>1.362<\/td>-0.373<\/td><\/tr>
Metsamor<\/td>0.243<\/td>-0.005<\/td>1.461<\/td>-0.727<\/td><\/tr>
Vorotan<\/td>0.083<\/td>-0.002<\/td>0.619<\/td>-0.225<\/td><\/tr>
Marzes<\/td>Aragatsotn<\/td>0.082<\/td>-0.008<\/td>0.706<\/td>-0.213<\/td><\/tr>
Ararat<\/td>-0.016<\/td>0.002<\/td>-0.157<\/td>0.041<\/td><\/tr>
Armavir<\/td>0.042<\/td>-0.004<\/td>0.357<\/td>-0.110<\/td><\/tr>
Gegharkunik<\/td>0.182<\/td>-0.018<\/td>1.180<\/td>-0.527<\/td><\/tr>
Kotayk<\/td>0.125<\/td>-0.012<\/td>1.089<\/td>-0.324<\/td><\/tr>
Lori<\/td>0.662<\/td>-0.066<\/td>2.901<\/td>-2.438<\/td><\/tr>
Shirak<\/td>0.234<\/td>-0.023<\/td>1.720<\/td>-0.643<\/td><\/tr>
Syunik<\/td>0.077<\/td>-0.008<\/td>0.532<\/td>-0.217<\/td><\/tr>
Tavush<\/td>0.590<\/td>-0.059<\/td>3.722<\/td>-1.728<\/td><\/tr>
Vayots Dzor<\/td>0.012<\/td>-0.001<\/td>0.084<\/td>-0.033<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

Using this ES as a case study, we tested the feasibility of assessing ES loss resulting from the historical conversion of natural grasslands by humans. The loss was assessed as the difference between the ES indicator values for the 2023 land cover and for a fully natural land-cover scenario in which all croplands and built-up areas are replaced by grasslands. ES loss is greatest\u2014both in absolute and relative terms\u2014in the Akhuryan watershed (a 5% decrease in runoff retention and a 10% increase in quick runoff), and smallest in the Arpa watershed (\u22120.7% and +2.7%, respectively) (Figure 31A4-9). Nonetheless, the results suggest that the ES has been mostly retained.

\"\"Figure 31A4-9. ES loss resulting from the historical conversion of natural grasslands by<\/strong><\/p>\n\n\n\n

As expected, the most significant loss of ES occurred in areas that are currently built-up where quick runoff increased the most\u2014by 49%. For croplands, the ES loss is less substantial (Figure 31A4-10). <\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Figure 31A4-10. ES loss loss in built-up areas and in croplands<\/strong><\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

We apologize for possible errors in the machine translation of the site Flood Risk Mitigation (InVEST UFRM model) GIS modeling and analysis, presentation of results – Eduard Kazakov (NextGIS O\u00dc, Estonia);Analysis and presentation of results – Elena Bukvareva (BCC-Armenia);Assessment of the alignment of results with real watersheds in Armenia – Vardan Asatryan (NAS RA) Assessment of the relevance of modeling results for […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":1545,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2485","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/pages\/2485","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/comments?post=2485"}],"version-history":[{"count":61,"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/pages\/2485\/revisions"}],"predecessor-version":[{"id":5123,"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/pages\/2485\/revisions\/5123"}],"up":[{"embeddable":true,"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/pages\/1545"}],"wp:attachment":[{"href":"https:\/\/biodiversity-armenia.am\/en\/wp-json\/wp\/v2\/media?parent=2485"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}